metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: mini-mlm-tweet-target-tweet
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tweet_eval
type: tweet_eval
config: emotion
split: train
args: emotion
metrics:
- name: Accuracy
type: accuracy
value: 0.7352941176470589
- name: F1
type: f1
value: 0.737654460370971
mini-mlm-tweet-target-tweet
This model is a fine-tuned version of muhtasham/mini-mlm-tweet on the tweet_eval dataset. It achieves the following results on the evaluation set:
- Loss: 1.4122
- Accuracy: 0.7353
- F1: 0.7377
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8264 | 4.9 | 500 | 0.7479 | 0.7219 | 0.7190 |
| 0.3705 | 9.8 | 1000 | 0.8205 | 0.7487 | 0.7479 |
| 0.1775 | 14.71 | 1500 | 1.0049 | 0.7273 | 0.7286 |
| 0.092 | 19.61 | 2000 | 1.1698 | 0.7353 | 0.7351 |
| 0.0513 | 24.51 | 2500 | 1.4122 | 0.7353 | 0.7377 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2